Martin Ruskov @mapto@qoto.org

Beef cattle production accounts for 3.7% of U.S. greenhouse gas emissions. Experts in cow burps and meat processing say the industry can become more sustainable by experimenting with virtual fencing, feed additives to reduce methane and using every part of the animal. https://theconversation.com/colorado-ranchers-and-consumers-can-team-up-to-make-beef-supply-chains-more-sustainable-272582

Mladenov – who has worked as a United Nations diplomat in the Middle East – is seen as an administrator, but one who may not be capable of pushing back against Israel and representing Palestinians in Gaza.

aljazeera.com/…/scepticism-hope-gaza-reacts-trump…

Academia loves to celebrate interdisciplinary research, but its career system quietly pushes many interdisciplinary scholars out.

https://theconversation.com/research-institutions-tout-the-value-of-scholarship-that-crosses-disciplines-but-academia-pushes-interdisciplinary-researchers-out-254034

College graduates earn $1.2 million more over their lifetime than high school graduates, and unemployment rates are half as high. But as skepticism about college grows, universities need to weave creativity and invention into undergraduate education to prove their value.

https://theconversation.com/financial-case-for-college-remains-strong-but-universities-need-to-add-creative-thinking-to-their-curriculum-269463

Schools have long taught that humans populated North America around 12K yrs ago by crossing the Bering land bridge. This story supports settler colonialism, and contradicts #Indigenous stories, which offer memories of human habitation here during the last glacial maximum.

Also, the Bering land bridge story falls apart when you find out about the century of archaeological evidence academia has vigorously suppressed.

Read more in my new essay. 👇

https://www.hcn.org/issues/58-1/what-does-time-immemorial-really-mean/

Why We Don't Use #AI

https://www.yarnspinner.dev/blog/why-we-dont-use-ai/

Great to see that @hennavirkkunen, the @EUCommission Vice-President for Tech Sovereignty, Security and Democracy joined Mastodon: Welcome!

There are now sufficiently many different examples of Erdos problems that have been resolved with various amounts of AI assistance and formal verification (see https://github.com/teorth/erdosproblems/wiki/AI-contributions-to-Erd%C5%91s-problems for a summary) that one can start to discern general trends.

Broadly speaking, we now see an empirical tradeoff between the level of AI involvement in the solution, and the difficulty or novelty of that solution. In particular, the recent solutions have spanned a spectrum roughly describable as follows:

1. Completely autonomous AI solutions to Erdos problems that are short and largely follow a standard technique. (In many, but not all, of these cases, some existing literature was found that proved a very similar result by a similar method.)

2. AI-powered modifications of existing solutions (which could be either human-generated or AI-generated) that managed to improve or modify these solutions in various ways, for instance by upgrading a partial solution to a full solution, or optimizing the parameters of the proof.

3. Complex interactions between humans and AI tools in which the AI tools provided crucial calculations, or proofs of key steps, allowing the collaboration to achieve moderately complicated and novel solutions to open problems.

4. Difficult research-level papers solving one or more Erdos problems by mostly traditional human means, but for which AI tools were useful for secondary tasks such as generation of code, numerics, references, or pictures.

(1/2)

See here for examples:

bsky.app/…/unitedkingdom.feddit.uk.ap.brid.gy
retrolemmy.com/post/31790836/17287584

There is still more testing and development needed, check the issue for more details.